MRI-Based Classification Models in Prediction of Mild Cognitive Impairment and Dementia in Late-Life Depression

被引:64
作者
Lebedeva, Aleksandra K. [1 ]
Westman, Eric [1 ]
Borza, Tom [2 ,3 ]
Beyer, Mona K. [4 ]
Engedal, Knut [5 ,6 ]
Aarsland, Dag [1 ,7 ,8 ]
Selbaek, Geir [2 ,3 ,5 ,6 ]
Haberg, Asta K. [9 ,10 ]
机构
[1] Karolinska Inst, Dept Neurobiol Care Sci & Soc, Stockholm, Sweden
[2] Innlandet Hosp Trust, Ctr Old Age Psychiat Res, Brumunddal, Norway
[3] Univ Oslo, Fac Med, Inst Clin Med, Oslo, Norway
[4] Oslo Univ Hosp, Rigshosp, Dept Radiol & Nucl Med, Oslo, Norway
[5] Oslo Univ Hosp, Dept Geriatr Med, N-0450 Tonsberg, Norway
[6] Oslo & Norwegian Natl Advisory Unit Aging & Hlth, Tonsberg, Norway
[7] Kings Coll London, Inst Psychiat Psychyol & Neurosci, Dept Old Age Psychiat, London, England
[8] Stavanger Univ Hosp, Ctr Age Related Med, Stavanger, Norway
[9] Norwegian Univ Sci & Technol, Dept Neurosci, Trondheim, Norway
[10] St Olavs Univ Hosp, Dept Radiol & Nucl Med, Trondheim, Norway
关键词
depression; MCI; Alzheimer's disease; Freesurfer; neurodegeneration; hypothalamus; ventral diencephalon; depressive episodes; ALZHEIMERS-DISEASE; HIPPOCAMPAL ATROPHY; MAJOR DEPRESSION; BASAL FOREBRAIN; STRESS; BRAIN; DISORDER; RELIABILITY; METABOLISM; FLUOXETINE;
D O I
10.3389/fnagi.2017.00013
中图分类号
R592 [老年病学]; C [社会科学总论];
学科分类号
03 ; 0303 ; 100203 ;
摘要
Objective: Late-life depression (LLD) is associated with development of different types of dementia. Identification of LLD patients, who will develop cognitive decline, i.e., the early stage of dementia would help to implement interventions earlier. The purpose of this study was to assess whether structural brain magnetic resonance imaging (MRI) in LLD patients can predict mild cognitive impairment (MCI) or dementia 1 year prior to the diagnosis. Methods: LLD patients underwent brain MRI at baseline and repeated clinical assessment after 1-year. Structural brain measurements were obtained using Freesurfer software (v. 5.1) from the T1W brain MRI images. MRI-based Random Forest classifier was used to discriminate between LLD who developed MCI or dementia after 1-year follow-up and cognitively stable LLD. Additionally, a previously established Random Forest model trained on 185 patients with Alzheimer's disease (AD) vs. 225 cognitively normal elderly from the Alzheimer's disease Neuroimaging Initiative was tested on the LLD data set (ADNI model). Results: MCI and dementia diagnoses were predicted in LLD patients with 76%/68%/84% accuracy/sensitivity/specificity. Adding the baseline Mini-Mental State Examination (MMSE) scores to the models improved accuracy/sensitivity/specificity to 81%/75%/86%. The best model predicted MCI status alone using MRI and baseline MMSE scores with accuracy/sensitivity/specificity of 89%/85%/90%. The most important region for all the models was right ventral diencephalon, including hypothalamus. Its volume correlated negatively with the number of depressive episodes. ADNI model trained on AD vs. Controls using SV could predict MCI-DEM patients with 67% accuracy. Conclusion: LDD patients developing MCI and dementia can be discriminated from LLD patients remaining cognitively stable with good accuracy based on baseline structural MRI alone. Baseline MMSE score improves prediction accuracy. Ventral diencephalon, including the hypothalamus might play an important role in preservation of cognitive functions in LLD.
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页数:11
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